Belajar Geostats
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Updated
Apr 15, 2024 - JavaScript
Belajar Geostats
Python package for automated scraping, cleaning, and AI-driven classification of new drug approvals. Harness OpenAI's GPT-3.5 Turbo to transform complex data into actionable insights
Repository containing projects and algorithms developed for the INF01124 - Data Classification and Search Algorithms course at UFRGS.
displaying perceptron algorithm to its core
In this case study, a decision tree is build to predict the income of a given population, which is labelled as <= 50𝐾𝑎𝑛𝑑> 50K on the basis of various attributes (predictors) like age, working class type, marital status, gender, race etc.
Predicting MLB Hall of Fame status based on career statistics and accolades.
This project is a simplified version of TensorFlow, which uses a neural network to predict the price of homes in the Boston area
A tool for aggregating and crowd-sourcing the classification emergency call data
Classification of Gamma and Hadron events by training classifieres and machine learning algorithms on the MAGIC Gamma Telescope dataset.
Desktop application helping with TPR/FPR calculations and visualize ROC curve based provided parameters.
BackordersPredcition
This repository is a Virtual Internship contains impressive projects related to Machine Learning.
Building multi models to classify numerical data of Gamma, Hadron dataset
This data analysis notebook demonstrates lossless, lossy visualizations techinques, and classification methods. We demonstrate analysis of scientific data on hot-swappable datasets.
Here You can get access to all my data analysis projects.
SAWO-NN
4-Weeks Data Science Internship at Oasis Infobyte
This project uses a neural network to classify the sentiment of a review as positive or negative
Library for one-dimensional data classification and simple statistics in Rust
In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using Python, and Azure Notebooks.
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